Related Experiment Videos
Radiobiological indices that consider volume: a review
L Holloway1, P Hoban, P Metcalfe
1Department of Radiation Oncology, Liverpool Hospital, BC, NSW. Lois.Holloway@swsahs.nsw.gov.au
Australasian Physical & Engineering Sciences in Medicine
|September 11, 2002
Summary
Predicting radiotherapy outcomes requires understanding treatment volume. This review examines models using volume data to improve tumor control probability and normal tissue complication probability, aiding clinical decisions.
Area of Science:
- Radiation oncology
- Medical physics
- Radiobiology
Background:
- Accurate prediction of radiotherapy outcomes is crucial for effective cancer treatment and minimizing side effects.
- Treatment volume is a key factor influencing both tumor eradication and normal tissue damage.
Purpose of the Study:
- To review the current use and accuracy of models incorporating treatment volume in radiotherapy.
- To build upon previous work on fractionation and the linear quadratic model.
Main Methods:
- Assessment of various models that utilize volume information, including dose volume histograms (DVHs).
- Evaluation of reduction schemes and adjustments to tumor control probability (TCP) and normal tissue complication probability (NTCP) models.
Main Results:
- Dose volume histograms provide useful volume information but are difficult to correlate directly with treatment plans.
- Models incorporating volume data, such as adjusted TCP and NTCP models, have shown clinical utility.
Conclusions:
- Volume is critical for assessing radiotherapy's impact on clonogenic cells and normal tissues.
- While current volume-based models are useful, their accuracy is constrained by the availability of radiobiological data.